产业发展，人工智能开辟社会经济新赛道。当前，人工智能作为引领新一轮科技革命和产业变革的核心 驱动力，正以跨界融合的态势渗透到经济社会各领域。在制造业，智能机器人、数字技术实现生产流程 自动化与精准化管控，推动"中国制造"向"中国智造"转型；在服务业，智能客服、个性化推荐算法正在 重构消费场景与服务模式，提升供给与需求的匹配效率；在农业领域，智慧灌溉、病虫害智能监测系统 助力农业现代化提质增效；在法律行业，智能合约审查、类案检索平台赋能法律实务高效开展，推动法 律服务向专业化、普惠化发展。从制造业的智能生产、服务业的精准服务到公共领域的治理革新，从数 字经济的业态创新到实体经济的提质增效，人工智能通过数据要素与产业要素的深度融合，重构了产业 价值链、创新链与人才链，推动社会生产力实现质的飞跃。 张菊玲 党的二十届四中全会通过的《中共中央关于制定国民经济和社会发展第十五个五年规划的建议》把"深 入推进数字中国建设"确立为"十五五"时期经济社会发展的重大任务目标，明确提出"全面实施'人工智 能+'行动""全方位赋能千行百业"。这些战略部署，明确了人工智能作为数字中国建设重要引擎的战略 定位，为包括高等教育在内的教育 ...

Core Insights - The report from Guosen Securities emphasizes the importance of AI education products that can deliver full-chain service and effectively enhance teaching quality [1] - The evolution of online education provides valuable lessons for AI education, which now faces a more severe supply-demand mismatch post "double reduction" policy [1][2] - The commercial model of online education has shifted towards live courses that can frequently meet user needs and directly impact teaching outcomes [2] Group 1: AI Education Development - AI education must achieve a closed-loop service of "teaching-learning-practice-evaluation" and verifiable teaching results [1] - The demand for AI interactive classes and problem-solving systems is particularly strong among high school and adult learners, who are self-driven and have clear quantifiable outcomes [1][3] - For younger students, AI education serves as a compliant resource post "double reduction," integrating realistic simulation classrooms and emotional interaction technology to improve teaching effectiveness [1] Group 2: Online Education Business Model Changes - Online education companies with valuations exceeding 100 billion are concentrated in the live course sector, which offers strong teaching effectiveness and full-chain delivery [2] - Historical online education products have transitioned from various formats to focus on live courses due to their ability to directly impact learning outcomes [2] - The shift in AI education products should move from single tools to a comprehensive service model encompassing "teaching-practice-testing-feedback" while emphasizing learning outcome conversion [2] Group 3: Differentiated Design in AI Education - AI education products must cater to different age groups and needs, with younger students requiring engaging and participatory experiences [3] - High school and adult learners focus on efficiency, result verification, and cost-effectiveness, with tools designed for precise knowledge reinforcement [3] - Hardware solutions like smart learning tablets are in high demand but face challenges due to high costs and long repurchase cycles, indicating ongoing optimization in business models [3]